Apparatus, method and program for 3D data analysis, and microparticle analysis system

ABSTRACT

In an example embodiment, may be embodied in a data analysis apparatus comprises a control unit configured to provide data representative of a three dimensional image, the three dimensional image including at least a three dimensional coordinate space which includes at least one plane that divides the three dimensional coordinate space into at least two regions, a display unit configured to produce the three dimensional image based on the data representative of the three dimensional image, and an input unit configured to provide data representative of at least one of a movement and a position of the at least one plane. In other example embodiments, the present disclosure may be embodied in a data analysis server, a data analysis system, and/or a computer readable medium.

CROSS REFERENCES TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.14/349,893, filed Apr. 4, 2014, which is a national stage ofInternational Application No. PCT/JP2012/006428 filed on Oct. 5, 2012,which claims priority to Japanese Patent Application No. 2011-226675,filed on Oct. 14, 2011, the entire disclosure of each of which is herebyincorporated by reference herein.

BACKGROUND

The present technique relates to an apparatus, a method and a programfor a 3D data analysis, and to a microparticle analysis system. Moreparticularly, the present technique relates to a 3D data analysisapparatus that can display measurement data of microparticles in theform of a 3D stereoscopic image, and that can perform an analysis ofdata, such as population information, by using the 3D stereoscopicimage.

For analyzing microparticles, e.g., biologically-relevant particles suchas cells, microorganisms, and liposomes, and synthetic particles such aslatex particles, gel particles, and other particles for industrial uses,a microparticle measurement apparatus is employed which optically,electrically or magnetically measures the microparticles by introducinga dispersion liquid of the microparticles into a flow passage.

As one example, there is a particle analyzer for discriminatingsynthetic particles depending on sizes and shapes thereof. Parameters(variables) measurable by the particle analyzer are, e.g., elementcompositions and particle diameters of the microparticles.

Further, a flow cytometer (flow cytometry) is used in an analysis of thebiologically-relevant particles. Parameters measurable by the flowcytometer are, e.g., forward scattered light (FS), side-way scattering(SS), fluorescence (FL) and impedance of microparticles. The forwardscattered light (FS), the side-way scattering (SS), and the fluorescence(FL) are used as parameters indicating optical characteristics of cellsand microorganisms (both of which are referred to simply as “cells”hereinafter), and the impedance is used as a parameter indicatingelectrical characteristics of cells.

More specifically, first, the forward scattered light is light that isscattered forward at a small angle with respect to an axis of laserlight. The forward scattered light includes scattered light, diffractedlight, and refracted light, which are generated from the laser light ata cell surface. The forward scattered light is primarily used as aparameter indicating the size of the cell. Next, the side-way scatteringis light scattered at an angle of about 90 degrees with respect to theaxis of the laser light, and such scattered light is generated upon thelaser light impinging against a granule, a nucleus, etc. within a cell.The side-way scattering is primarily used as a parameter indicating aninternal structure of the cell. Further, the fluorescence is lightgenerated from a fluorescence dye labeled in a cell. The fluorescence isused as a parameter indicating, e.g., the presence or the absence of acell surface antigen recognized by an antibody that is labeled by thefluorescence dye, and an amount of nucleic acids to which thefluorescence dye is coupled. Moreover, the impedance is measured by theelectric resistance method and is used as a parameter indicating thevolume of the cell.

For analyzing data measured by the flow cytometer, a data analysisapparatus is employed which creates and displays a chart representing acharacteristic distribution of cells within a cell mass by plottingmeasurement values of the individual cells with any of the measurementparameters set on a coordinate axis. A one-dimensional distributionchart including one measurement parameter is also called a histogramthat is created as a graph with the measurement parameter set on anX-axis and a cell number (count) set on a Y-axis. Furthermore, atwo-dimensional distribution chart including two measurement parametersis also called a cytogram. The cytogram is created by plottingindividual cells, based on measurement values of the cells, in acoordinate plane in which one measurement parameter is set on an X-axisand the other measurement parameter is set on a Y-axis.

By setting regions on the histogram or the cytogram, statistical datacan be obtained regarding cells present in each region. A commonly usedexample of the statistical data is a frequency distribution (populationinformation) representing at what a rate target cells are contained in acell mass. The frequency distribution is calculated as a rate at whichcells present in each region set on the histogram or the cytogram occupyin the entire cell mass.

For example, when it is known that the target cell exhibits a value ofnot less than a certain value for a predetermined parameter, a processof calculating a distribution frequency of the target cell based on thehistogram is started by dividing the histogram into two parts at thecertain value on an X-axis. With the division, the histogram ispartitioned into a region where the parameter is not less than thecertain value (i.e., a region where the target cell exists) and a regionwhere the parameter is less than the certain value (i.e., a region wherenon-target cells exist). A data analysis apparatus calculates, for eachof the set regions, the distribution frequency from the number of thecells present in the relevant region. Also, in the case using thecytogram, a process of calculating a distribution frequency is startedby dividing the cytogram into four regions at the certain value on eachof an X-axis and a Y-axis. With the division, the cytogram ispartitioned into a region where two parameters are both not less thanthe certain value (i.e., a region where the target cell exists) and aregion where at least one of the two parameters is less than the certainvalue (i.e., a region where non-target cells exist).

PTL 1 proposes “An analysis apparatus comprising measurement dataacquisition means for acquiring first, second and third measurement datafrom an analyte, three-dimensional distribution map creation means forcreating a three-dimensional distribution map that represents adistribution of a formed element, which is contained in the analyte,with the first, second and third measurement data set on axes, regionsetting means for setting a demarcated region on the three-dimensionaldistribution map in a changeable manner, and reference distribution mapcreation means for creating, for the formed element belonging to thedemarcated region set by the region setting means, at least one of atwo-dimensional distribution map with the first and second measurementdata set on axes and a frequency distribution map with the firstmeasurement data set on an axis” (see Claim 9 of PTL 1). According tothe proposed analysis apparatus, the demarcated region can be set on thethree-dimensional distribution map while referring to thetwo-dimensional distribution map (cytogram) and the frequencydistribution map (histogram), which maps are displayed along with thethree-dimensional distribution map. Additionally, the three-dimensionaldistribution map in the proposed analysis apparatus is displayed in aplanar view on a display, and it is not displayed in a stereoscopicview.

In relation to the present technique, the binocular stereoscopic solidimage technique (3D stereoscopic image technique) will be describedbelow. To produce a binocular stereoscopic solid image, two images arefirst prepared which are obtained when looking at an object by a righteye and a left eye, respectively. Then, those two images are displayedat the same time such that the image for the right eye is displayed toonly the right eye and the image for the left eye is displayed to onlythe left eye. As a result, an image perceived by eyes of a user whenlooking at the object in a three-dimensional space is reproduced, thusenabling the user to perceive the object in a stereoscopic view.

3D displays capable of providing a stereoscopic view are mainlypracticed as (a) spectacle type, (b) naked eye type, and (c) viewertype. Of those types, (a) spectacle type is further classified into ananaglyph type, a polarization filter type, and a time division type.Also, (b) naked eye type is classified into a parallax barrier type anda lenticular type, and (c) viewer type is classified into a stereoscopetype and a head mount type.

CITATION LIST Patent Literature

PTL 1: Japanese Unexamined Patent Application Publication No. 2006-17497

Non Patent Literature

NPL 1: A New “Logicle” Display Method Avoids Deceptive Effects ofLogarithmic Scaling for Low Signals and Compensated Data, Cytometry PartA 69A:541-551, 2006.

SUMMARY

On a histogram with one measurement parameter set on an axis or on acytogram with one combination of measurement parameters set on axes,there is often a region where a small mass of cells to be analyzed andunwanted cells overlap with each other. For example, when lymphocytesare to be analyzed by using human peripheral blood as a sample, somemonocytes and the lymphocytes are often present in the same region on acytogram in which the forward scattered light (FS) and the side-wayscattering (SS) are set on axes.

In the known data analysis using the histogram and the cytogram,therefore, a difficulty resides in specifying a target cell and insetting a region where only the target cell is present. Thus,statistical data, such as a frequency distribution, cannot be obtainedat high accuracy.

Accordingly, a primary object of the present technique is to provide adata analysis apparatus that enables a user to easily and intuitivelyspecify microparticles to be analyzed or a small mass of themicroparticles on a distribution map, and to obtain accurate statisticaldata of the microparticles or the small mass of the microparticle.

In an example embodiment of the present disclosure, a data analysisapparatus comprises: a control unit configured to provide datarepresentative of a three dimensional image, the three dimensional imageincluding at least a three dimensional coordinate space which includesat least one plane that divides the three dimensional coordinate spaceinto at least two regions; a display unit configured to produce thethree dimensional image based on the data representative of the threedimensional image; and an input unit configured to provide datarepresentative of at least one of a movement and a position of the atleast one plane.

In another example embodiment, a data analysis server comprises: a datastorage unit configured to store measurement data; and a data processingunit configured to create data representative of a three dimensionalimage based on the measurement data, the three dimensional imageincluding at least a three dimensional coordinate space which includesat least one plane that divides the three dimensional coordinate spaceinto at least two regions, wherein the at least one plane is moveablebased on data representative of at least one of a movement and aposition of the at least one plane received from an input device.

In another example embodiment, a data analysis system comprises: ameasurement apparatus; and a data analysis apparatus including: acontrol unit configured to provide data representative of a threedimensional image, the three dimensional image including at least athree dimensional coordinate space which includes at least one planethat divides the three dimensional coordinate space into at least tworegions; a display unit configured to produce the three dimensionalimage based on the data representative of the three dimensional image;and an input unit configured to provide data representative of at leastone of a movement and a position of the at least one plane.

In another example embodiment, a data analysis system comprises: ameasurement apparatus; and a data analysis apparatus including: acontrol unit configured to provide data representative of a threedimensional image, the three dimensional image including at least athree dimensional coordinate space which includes at least one planethat divides the three dimensional coordinate space into at least tworegions; a display unit configured to produce the three dimensionalimage based on the data representative of the three dimensional image;and an input unit configured to provide data representative of at leastone of a movement and a position of the at least one plane.

In another example embodiment, a computer readable medium storesinstructions which, when executed, cause a data analysis apparatus to:provide data representative of a three dimensional image, the threedimensional image including at least a three dimensional coordinatespace which includes at least one plane that divides the threedimensional coordinate space into at least two regions; and receive aninput providing data representative of at least one of a movement and aposition of the at least one plane.

In the present technique, the term “microparticle” may include a varietyof microparticles, e.g., biologically-relevant particles such as cells,microorganisms, and liposomes, and synthetic particles such as latexparticles, gel particles, and other particles for industrial uses.

The cells may include animal cells (blood cells) and plant cells. Theorganisms include, e.g., bacteria such as coli bacteria, viruses such asa tobacco mosaic virus, and fungi such as a yeast cell. Thebiologically-relevant particles include, e.g., chromosomes, liposomes,mitochondria, and organelle (cell organelle), which constitute variouscells. The biologically-relevant particles may further include, e.g.,nucleic acids, proteins, and biologically-relevant high molecules suchas complexes of the formers. The particles for industrial uses mayinclude, e.g., organic or inorganic high-molecular materials, andmetals. The organic high-molecular materials include, e.g., polystyrene,styrene divinylbenzen, and polymethyl methacrylate. The inorganichigh-molecular materials include, e.g., glass, silica, and magneticmaterials. The metals include, e.g., gold colloid and aluminum. Shapesof those microparticles are generally spherical, but the shapes may beaspherical. In addition, the size, the mass, etc. of the microparticleare not limited to particular ones.

According to an example embodiment of the present disclosure, a dataanalysis apparatus is provided which may enable a user to easily andintuitively specify microparticles to be analyzed or a small mass of themicroparticles on a distribution map, and to obtain accurate statisticaldata of the microparticles or the small mass of the microparticles.

Additional features and advantages are described herein, and will beapparent from the following Detailed Description and the figures.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a block diagram to explain a configuration of a 3D dataanalysis apparatus according to the present technique, which is disposedin association with a flow cytometer.

FIG. 2 is a block diagram to explain a functional configuration of the3D data analysis apparatus according to the present technique.

FIG. 3 is an illustration to explain a three-dimensional distributionmap displayed by the 3D data analysis apparatus according to the presenttechnique.

FIG. 4 is an illustration to explain a binocular stereoscopic solidimage (3D stereoscopic image) displayed by the 3D data analysisapparatus according to the present technique.

FIG. 5 is an illustration to explain a plane (guide plane) and regions,which are set in a coordinate space of the three-dimensionaldistribution map.

FIG. 6 is an illustration to explain a three-dimensional distributionmap in which the coordinate space is partitioned into eight regions.

FIGS. 7A and 7B are illustrations to explain arrangement of indicatorfigures used for moving the guide plane to partition the coordinatespace of the three-dimensional distribution map into the eight regions.

FIG. 8 is an illustration to explain a guide plane that is obliquely setin the coordinate space of the three-dimensional distribution map.

FIG. 9 is a table to explain a display example of analysis results of afrequency distribution in the three-dimensional distribution map inwhich the coordinate space is partitioned into the eight regions.

FIGS. 10A and 10B are illustrations to explain a three-dimensionaldistribution map that is displayed in multiple colors by reflecting thedistribution frequency.

FIGS. 11A and 11B are illustrations to explain shapes of a figurecorresponding to the microparticle in the 3D stereoscopic image.

FIG. 12 is a conceptual view to explain a stereoscopic observation imageof the figure that has been subjected to a shading process.

FIGS. 13A through 13C are illustrations to explain a method forexecuting the shading process.

FIG. 14 is a conceptual view to explain a stereoscopic observation imageof a coordinate axis.

FIGS. 15A through 15C are conceptual views to explain a stereoscopicobservation image of the three-dimensional distribution map when viewedin a direction of each coordinate axis.

FIG. 16 is a conceptual view to explain a stereoscopic observation imagedisplayed as a moving image in which a figure corresponding to amicroparticle swings.

DETAILED DESCRIPTION

Embodiments of the present application will be described below in detailwith reference to the drawings. It is to be noted that the embodimentdescribed below is one of typical embodiments of the present techniqueand is not to be construed as limiting the scope of the presenttechnique. The following description is made in order listed below:

1. Configuration of 3D data analysis apparatus

2. Display of 3D stereoscopic image

3. Data analysis

4. Display of data

5. Features of 3D stereoscopic image

-   -   (5-1) Shape of figure    -   (5-2) Shading process of figure    -   (5-3) Coordinate axis    -   (5-4) Moving image

6. 3D data analysis program

1. Configuration of 3D Data Analysis Apparatus

FIG. 1 illustrates a hardware configuration of a 3D data analysisapparatus according to the present technique. In the embodimentdescribed here, the 3D data analysis apparatus is disposed inassociation with a microparticle measurement apparatus, thusconstituting a microparticle analysis system. Further, FIG. 2illustrates a functional configuration of the microparticle analysissystem. The following description is made, by way of example, inconnection with the case where a flow cytometer is used as themicroparticle measurement apparatus.

A 3D data analysis apparatus denoted by symbol 1 in the drawings isconnected to a flow cytometer 2 by a communication cable 4, therebyconstituting a microparticle analysis system 3. The 3D data analysisapparatus 1 includes a central processing unit (CPU) 10, a memory 20, ahard disk 30, a user interface, etc. The hard disk 30 stores and holdstherein a 3D data analysis program 31, microparticle measurement data32, an operating system (OS) 33, etc. The user interface includes, forexample, a mouse 41 and a keyboard 42 for accepting input of informationfrom a user, and a display 43 and a printer 44 for outputtinginformation to the user. Other input devices, such as a stick controllerand a pen tablet, may be disposed instead of or in addition to the mouse41 and the keyboard 42.

A data storage unit 130 (hard disk 30) stores the microparticle (cell)measurement data 32 output from the flow cytometer 2. The measurementdata output from an input/output interface 250 of the flow cytometer 2is input to an input/output interface 150 of the 3D data analysisapparatus 1 via the communication cable 4 and is stored in the datastorage unit 130 (hard disk 30).

The measurement data 32 is processed in a data processing unit 120. Thedata processing unit 120 starts processing upon receiving a user's inputfrom an input unit 141 (e.g., the mouse 41 or the keyboard 42). In moredetail, when three independent variables (parameters) are selected fromthe measurement data 32 and input by the user, the data processing unit120 creates a three-dimensional distribution map that represents acharacteristic distribution of microparticles with the selectedparameters set on coordinate axes. The three-dimensional distributionmap is created by plotting the microparticles in a coordinate space inwhich the selected parameters are set on the coordinate axes. Themicroparticles are plotted by computing, from measurement values of theselected parameters, respective positions and shapes of themicroparticles within the coordinate space, and by drawing the computedshapes at the computed positions.

Here, the term “independent parameters” implies different parametersselected from among, for example, forward scattered light (FS), side-wayscattering (SS), fluorescence (FL), and impedance of the microparticles.The fluorescence (FL) can be handled as a parameter that is differentfor each of wavelength ranges of fluorescence dyes labeled on themicroparticles. Those fluorescence parameters are expressed as FL1, FL2to FLn (n is an integer being equal to 3 or more). Examples of the threeindependent parameters include a combination of the forward scatteredlight (FS), the side-way scattering (SS), and the fluorescence (FL1),and a combination of the forward scattered light (FS), the side-wayscattering (SS), and the impedance. Other combinations of the threeindependent parameters can also be set by optionally selecting properparameters from the measurement data.

The three-dimensional distribution map created by the data processingunit 120 is displayed as a 3D stereoscopic image on a display unit 142(e.g., the display 43). One or plural 3D stereoscopic images can bedisplayed on the display unit 142. When two or more 3D stereoscopicimages are displayed, it is possible to display the 3D stereoscopicimages that are observed in plural different directions for the samethree-dimensional distribution map, or to display the 3D stereoscopicimages of plural three-dimensional distribution maps in which at leastone of the selected three parameters differs from one another. Each 3Dstereoscopic image is displayed as a binocular stereoscopic solid imagedescribed in detail below.

Moreover, when the measurement data 32 includes values measured atplural different times (time points), the display unit 142 may display,as 3D stereoscopic images, three-dimensional distribution mapsrepresenting characteristic distributions of the microparticles at theplural time points. The measurement data including values measured atplural different time points is, for example, data obtained by measuringassociation or dissociation of a molecular complex on the cell surfaceover time by using the fluorescence resonance energy transfer (FRET)method, data obtained by measuring change of a cell membrane over timeby using a fluorescence dye of which fluorescence wavelength is changedcorresponding to electric charges of the cell membrane, or data obtainedby measuring the expression intensity of a cell surface molecule incorrelation to an influx response of intracellular calcium.

The 3D stereoscopic images of the three-dimensional distribution maps atthe plural time points may be displayed side by side at a time, ordisplayed one by one in a switching manner. When the 3D stereoscopicimages are displayed in a switching manner, the switching from one toanother image may be performed automatically or in accordance with aninput signal from the user. By displaying the 3D stereoscopic images ofthe three-dimensional distribution maps at the plural time points, theuser can perform a data analysis while confirming change in thecharacteristic distribution of the microparticles over time, and canmake a more multiple analysis including time (time axis) in addition tothe three parameters (coordinate axes).

The 3D stereoscopic image displayed on the display unit 142 may beoptionally rotated, enlarged or reduced in accordance with the user'sinput signal from the input unit 141 (e.g., the mouse 41 or the keyboard42). Further, when a demarcated region for gating or an analysis regionfor a later-described data analysis is set in the coordinate space ofthe three-dimensional distribution map in accordance with the inputsignal from the input unit 141, the 3D stereoscopic image is rotated,enlarged or reduced together with a stereoscopic shape, which isdisplayed in the 3D stereoscopic image to represent the demarcatedregion or the analysis region.

The flow cytometer 2 may have a configuration similar to orappropriately modified from that of the known flow cytometer. Morespecifically, the flow cytometer 2 includes a control unit 210, a flowsystem 220, a detection system 230, an input/output interface 250, etc.

In the flow system 220, a sample-liquid laminar flow containingmicroparticles is introduced into a flow passage, which is formed in aflow cell or a microchip, to flow through a center of a sheath-liquidlaminar flow such that the microparticles are arrayed in line within thelaminar flow. The detection system 230 acquires parameter valuesindicating characteristics of the microparticles flowing through theflow passage. In more detail, an optical detection unit 231 emits lightto the microparticles flowing through the flow passage, detectsscattered light and/or fluorescence generated from the microparticles,and obtains the intensity of the scattered light and/or thefluorescence. The optical detection unit 231 includes, for example, alaser light source, lenses, mirrors, and a filter, as well as an areaimaging device, e.g., a CCD or CMOS device, or a PMT (photo-multipliertube). Further, an electrical detection unit 232 includes an electrodedisposed to face the microparticles flowing through the flow passage anddetects an impedance, a capacity value (capacitance), an inductance,etc. of the microparticle. The flow cytometer 2 may include afractionation system 240 for fractionating the microparticles on whichit has been determined, as a result of the analysis, that themicroparticles have the desired characteristic. The fractionation system240 may be, for example, of the type that a droplet containing themicroparticles is ejected to a space outside the flow cell and only thedesired microparticles are recovered into a container by controlling amoving direction of the droplet.

Measurement values of the intensity of the scattered light and thefluorescence or measurement values of the impedance, the capacity value(capacitance), the inductance, etc., which have been detected in thedetection system 230, are converted to electrical signals and areoutput, as the measurement data, from the input/output interface 250.

2. Display of 3D Stereoscopic Image

FIG. 3 illustrates a three-dimensional distribution map displayed by the3D data analysis apparatus according to the present technique. Thethree-dimensional distribution map illustrated in FIG. 3 is displayed asa 3D stereoscopic image on the display unit 142 to be visuallyrecognized by the user in a stereoscopic view.

A three-dimensional distribution map 5 represents a characteristicdistribution of microparticles in a coordinate space 6 in which threeparameters selected by the user are set respectively on coordinate axes.In the three-dimensional distribution map 5, a figure 7 corresponding toeach microparticle is drawn at a position that is computed from themeasurement values of the selected parameters.

FIG. 3 illustrates, for example, the case where the three parameters areset as a combination of the forward scattered light (FS-Lin: X-axis),the side-way scattering (SS-Lin: Y-axis), and the first fluorescence(FL1-Lin: Z-axis). The parameters set on the coordinate axes may be acombination of optionally selected parameters. For example, the firstfluorescence (FL1), the second fluorescence (FL2), and the impedance maybe set on the X-axis, the Y-axis, and the Z-axis, respectively.

The 3D stereoscopic display of the three-dimensional distribution map 5is performed by using a binocular stereoscopic solid image. FIG. 4illustrates a binocular stereoscopic solid image displayed by the 3Ddata analysis apparatus according to the present technique.

When the parameters are selected by the user, the data processing unit120 creates the three-dimensional distribution map 5 and then creates animage when looking at the distribution map by a left eye (i.e., aleft-eye image 5L) and an image when looking at the distribution map bya right eye (i.e., a right-eye image 5R). The display unit 142 (e.g.,the display 43) displays the left-eye image 5L and the right-eye image5R at the same time such that the left-eye image 5L is presented to theleft eye and the right-eye image 5R is presented to the right eye in aseparated manner.

In the case of the time division type as one example of the spectacletype, the separate presentation can be performed by alternatelydisplaying the left-eye image 5L and the right-eye image 5R at a slighttime difference therebetween, and by synchronizing shutter spectacles 8with the alternating display of those images. In addition, the separatepresentation may be performed by using any of the other spectacle types,such as the anaglyph type and the polarization filter type, the nakedeye types, such as the parallax barrier type and the lenticular type,and the viewer types, such as the stereoscope type and the head mounttype.

By separately presenting the left-eye image 5L and the right-eye image5R, the display 43 reproduces an image to be perceived by the eyes ofthe user when looking at the three-dimensional distribution map in thethree-dimensional space, thus enabling the user to see the distributionmap in a stereoscopic view.

3. Data Analysis

The analysis region for the data analysis is set by the user who sets aplane, which partitions the coordinate space 6 of the three-dimensionaldistribution map 5 into plural regions, by employing the input device,e.g., the mouse 41 or the keyboard 42, while looking at the 3Dstereoscopic image displayed on the display unit 142. FIG. 5 illustratesconcrete examples of the set plane and region. For the sake ofsimplicity, FIG. 5 illustrates the case where the coordinate space 6 ispartitioned along one coordinate axis X into two regions 61 and 62 by aplane (hereinafter referred to also as a “guide plane”) 51.

The guide plane 51 is perpendicular to the coordinate axis X and dividesthe coordinate space 6 into the region 61 and the region 62 in adirection of the coordinate axis X. By moving an indicator figure 511,which is arranged at an intersection of the guide plane 51 and thecoordinate axis X, with manipulation of the input device, e.g., themouse 41 or the keyboard 42, the guide plane 51 is moved together withthe indicator figure 511. Stated another way, when the indicator figure511 is moved on the coordinate axis X in accordance with an input signalfrom the input unit 141, the guide plane 51 is moved in the coordinatespace 6 and its position is changed corresponding to the movement of theindicator figure 511. In FIG. 5, an arrow indicates a moving directionof the indicator figure 511 on the coordinate axis X and a movingdirection of the guide plane 51 in the coordinate space 6.

In more detail, for example, when it is known that a target cellexhibits a value of not less than a certain value for a predeterminedparameter, the indicator figure 511 on the coordinate axis Xrepresenting the predetermined parameter is moved to the certain value.Further, corresponding to the movement of the indicator figure 511, theguide plane 51 is moved in the coordinate space 6, thereby partitioningthe coordinate space 6 into a region 62 of not less than the certainvalue (i.e., a region where the figure 7 corresponding to the targetcell exists) and a region 61 of less than the certain value (i.e., aregion where the figure 7 corresponding to a non-target cell exists).

In the 3D stereoscopic image, the guide plane 51 is displayedsemitransparent such that the user can observe the figure 7, which isobserved on the deeper side than the guide plane 51 (i.e., the figure 7positioned in the region 62 in the illustrate example), when looking atthe image in a stereoscopic view. Therefore, the user can visuallyrecognize the figure 7 on the deeper side than the guide plane 51through the semitransparent guide plane 51. Thus, for example, in tryingto discriminate the figure 7 corresponding to the target cell and thefigure 7 corresponding to the non-target cell on the basis of anappropriate coordinate position depending on a distribution situationinstead of a parameter value, the user can set the position of the guideplane 51 while visually recognizing the distribution of the figures 7 inthe direction of the coordinate axis X.

The guide plane 51 may be displayed in the 3D stereoscopic image onlywhen a signal is input from the input unit 141. This enables the user tomore clearly visually confirm the figure 7, which is observed on thedeeper side than the guide plane 51, when setting the guide plane 51.Moreover, the user can more easily recognize the coordinate axes andscales and numerals on the coordinate axes, which are observed on thedeeper side than the guide plane 51. A similar advantageous effect canalso be obtained by enabling the guide plane 51 to be selectivelydisplayed or not in the 3D stereoscopic image in accordance with theuser's input signal from the input unit 141. In such a case, whenadjusting the position of the guide plane 51, the user may display theguide plane 51 in the image. When confirming the position of the setguide plane 51 and regions partitioned by the set guide plane 51, theuser may select non-display of the guide plane 51 in the image.

The coordinate space 6 can be partitioned into two or more regionsdepending on data to be analyzed. While the number of regions is notlimited to a particular value, it is preferable to partition thecoordinate space 6 into eight regions by setting a guide planeperpendicular to each of the coordinate axes. FIG. 6 illustrates athree-dimensional distribution map in which the coordinate space 6 ispartitioned into eight regions.

Three guide planes 51, 52 and 53 are perpendicular to the X-, Y- andZ-coordinate axes, respectively, and the coordinate space 6 ispartitioned by those three guide planes into eight regions, i.e.,regions 61 to 68. Of the eight regions, for example, the region 61 is aregion where a value of a parameter set on the X-axis is larger than avalue corresponding to the position of an indicator figure 511, a valueof a parameter set on the Y-axis is smaller than a value correspondingto the position of an indicator figure 521, and a value of a parameterset on the Z-axis is smaller than a value corresponding to the positionof an indicator figure 531. As another example, the region 68 is aregion where a value of the parameter set on the X-axis is smaller thanthe value corresponding to the position of the indicator figure 511, avalue of the parameter set on the Y-axis is larger than the valuecorresponding to the position of the indicator figure 521, and a valueof the parameter set on the Z-axis is larger than the valuecorresponding to the position of the indicator figure 531.

As described above, the positions of the guide planes 51, 52 and 53 canbe changed respectively by moving the indicator figures 511, 521 and531, which are arranged at intersections of the coordinate axes and theguide planes 51, 52 and 53 (see FIG. 7(A)). Alternatively, an indicatorfigure 541 may be arranged, as an indicator figure for moving the guideplanes 51, 52 and 53, at an intersection of the three planes. In such acase, the positions of the guide planes 51, 52 and 53 can besimultaneously changed together by moving the indicator figure 541.

While the above description has been made in connection with the casewhere the guide plane is set as a plane perpendicular to the coordinateaxis, the guide plane may be set as a plane that is oblique to all thecoordinate axes instead of being perpendicular thereto (see FIG. 8).Also in such a case, a position and an inclination of the guide planecan be changed by moving indicator figures arranged respectively atintersections of the guide plane and the coordinate axes.

4. Display of Data

The data processing unit 120 calculates parameter values and/or adistribution frequency in each region, and displays information(analysis results) regarding the parameter values and/or thedistribution frequency on the display unit 142.

The information regarding each of the parameter values may be, e.g., aminimum value, a maximum value, a mean value, a median value, a standarddeviation, and a standard error for the figures 7 present in therelevant region. Also, the information regarding the distributionfrequency is a proportion at which the number of the figures 7 presentin the relevant region occupies in the number of the figures 7 presentin the entire coordinate space 6. The distribution frequency is useful,for example, as population information representing at what a ratetarget cells are contained in a cell mass.

FIG. 9 illustrates a display example of analysis results of thefrequency distribution in the three-dimensional distribution map inwhich the coordinate space 6 is partitioned into the eight regions. Thefollowing description is made in connection with the case where, in thethree-dimensional distribution map 5 including the regions 61 to 68 setas illustrated in FIG. 6, the first fluorescence (FL1), the thirdfluorescence (FL3), and the fifth fluorescence (FL5) are setrespectively as parameters on the X-axis, Y-axis, and Z-axis.

In a table of the analysis results illustrated in FIG. 9, for example, afield including FL1(+), FL3(−), and FL5(−) represents the analysisresult (15.6%) of the frequency distribution in the region 61 where ameasurement value of FL1 is larger than the value corresponding to theposition of the indicator figure 511, a measurement value of FL3 issmaller than the value corresponding to the position of the indicatorfigure 521, and a measurement value of FL5 is smaller than the valuecorresponding to the position of the indicator figure 531. As anotherexample, a field including FL1(−), FL3(+), and FL5(+) represents theanalysis result (7.7%) of the frequency distribution in the region 68where a measurement value of FL1 is smaller than the value correspondingto the position of the indicator figure 511, a measurement value of FL3is larger than the value corresponding to the position of the indicatorfigure 521, and a measurement value of FL5 is larger than the valuecorresponding to the position of the indicator figure 531.

The analysis results of the frequency distribution may be presented tothe user in the 3D stereoscopic image, which is displayed on the displayunit 142, by displaying the figures 7 in different regions in multiplecolors each of which is correlated to a predetermined range of thedistribution frequency. The distribution frequency and the color of thefigure 7 can be correlated with each other by employing the heat mapexpression that has hitherto been used to visualize frequencyinformation.

FIG. 10 illustrates a three-dimensional distribution map that isdisplayed in multiple colors by reflecting the distribution frequency.The three-dimensional distribution map illustrated in FIG. 10(A) is thesame as that illustrated in FIG. 6. It is thus assumed that thecoordinate space 6 is partitioned into the regions 61 to 68 by the guideplanes 51, 52 and 53, and that the distribution frequency in each regionis calculated as per illustrated in FIG. 9. FIG. 10(B) indicates a colorthat is assigned, depending on a numerical value of the distributionfrequency calculated for each region, to the figures 7 present in therelevant region. A darker color is assigned to a region where thedistribution frequency is higher, and a lighter color is assigned to aregion where the distribution frequency is lower.

In the three-dimensional distribution map illustrated in FIG. 10(A),based on the correlation between the distribution frequency and thecolor illustrated in FIG. 10(B), the figures 7 are displayed in a darkercolor in the region where the distribution frequency is higher (thedistribution frequency is highest in the region 63 of FIG. 6), and thefigures 7 are displayed in a lighter color in the region where thedistribution frequency is lower (the distribution frequency is lowest inthe region 67 of FIG. 6). Thus, the user can intuitively perceive theanalysis results of the frequency distribution by displaying, in the 3Dstereoscopic image, the figures 7 in the individual regions in differentcolors depending on the analysis results of the frequency distribution.

The distribution frequency and the color can be correlated with eachother by multicolor display using not only shades of a single color asdescribed above, but also different luminosities, saturations, or hues.For example, as with the known heat map expression, the distributionfrequency may be displayed in different colors, which are changed from awarm color to a cold color as the distribution frequency lowers, byassigning the warm color, e.g., red, to a region where the distributionfrequency is high, by assigning a neutral color, e.g., green, to aregion where the distribution frequency is medium, and by assigning thecold color, e.g., blue, to a region where the distribution frequency islow.

The calculation of the parameter values and/or the distributionfrequency in each region by the data processing unit 120 may be newlyexecuted in interlock with user's manipulation of the input device tomove the guide plane whenever the position of the guide plane is changedand the setting of the regions is made again. Furthermore, the newlycalculated distribution frequency is preferably reflected on the 3Dstereoscopic image, which is displayed on the display unit 142, byupdating the color of the figure 7 in each region of thethree-dimensional distribution map to the color corresponding to thecalculated distribution frequency whenever the calculation is executed.Thus, by displaying the analysis results of the distribution frequencyin the 3D stereoscopic image in real time responsive to the user'soperation of changing the position of the guide plane and setting theregions again, the user can more intuitively perceive the analysisresults, and this contributes to improving data analysis efficiency.

Other than the above-described method of automatically changing thecolor of the figure 7 in each region of the three-dimensionaldistribution map in interlock with the user's operation of changing theposition of the guide plane and setting the regions again, the user maychange the color of the figure 7 at desired timing, for example, afterchanging the position of the guide plane, to be able to confirm theanalysis results of the distribution frequency. In such a case, duringthe user's operation of changing the position of the guide plane andsetting the regions again, all the figures 7 in all the regions may bedisplayed in the same color, but the figures 7 in each of the regionsare preferably displayed in a specific color per region. For example, inthe three-dimensional distribution map where the coordinate space 6 ispartitioned into eight regions as illustrated in FIG. 6, the figures 7in the eight regions, i.e., the regions 61 to 68, are displayed indifferent specific colors. Thus, by displaying the figures 7 in thespecific color for each of the regions, the user can set the regionswhile confirming in which one of the regions the figure 7 is present,when changing the position of the guide plane, and can perform theaccurate setting of the regions while clearly recognizing the boundarybetween the regions. After the completion of, e.g., the change in theposition of the guide plane, preferably, the user changes the color ofthe figure 7 from the color specific to the relevant region to the colorreflecting the distribution frequency in the relevant region at desiredtiming so that the user can confirm the analysis results of thedistribution frequency.

In the 3D data analysis apparatus 1, as described above, the user canset the regions for the data analysis while looking at, in astereoscopic view, the three-dimensional distribution map in which threeoptionally selected parameters are set on the coordinate axes, and canobtain the analysis results of the variable values and/or thedistribution frequency in the set regions. With the 3D data analysisapparatus 1, therefore, even for a sample containing microparticles tobe analyzed, which are difficult to specify by using the known histogramor cytogram with one or two parameters set on one or two coordinateaxes, it is possible to set a region where only the microparticles to beanalyzed are present, and to obtain accurate analysis results. Further,information regarding three characteristics of the microparticle can beobtained with one graph by displaying the three-dimensional distributionmap in an optional combination of the parameters set on the coordinateaxes. In addition, more information can be obtained by displaying 3Dstereoscopic images of the same three-dimensional distribution map,which are observed from plural different directions, or 3D stereoscopicimages of plural three-dimensional distribution maps in which at leastone of three selected parameters is different from one another.Accordingly, the 3D data analysis apparatus 1 can reduce the number ofgraphs to be referred to in comparison with that in the known analysisusing the histogram or the cytogram, and can perform an efficientanalysis.

5. Features of 3D Stereoscopic Image

Features of the 3D stereoscopic image displayed by the 3D data analysisapparatus according to the present technique will be described below insuccessive order.

(5-1) Shape of Figure

The figure corresponding to the microparticle, denoted by symbol 7 inFIG. 3, is computed as a polyhedron made of a combination of polygonshaving predetermined shapes and is displayed in the 3D stereoscopicimage. As described above, the data processing unit 120 computes theposition of each microparticle in the coordinate space and the figure 7thereof on the basis of the measurement values of the parametersselected by the user, and creates a three-dimensional distribution map.At that time, a computation load of the data processing unit 120 can bereduced by computing the figure 7 on condition that the figure 7 is apolyhedron made of a combination of polygons having predeterminedshapes. Moreover, a stereoscopic effect in appearance of the image canbe improved in a stereoscopic view by displaying, in the 3D stereoscopicimage, the figure as a polyhedron made of a combination of polygonshaving predetermined shapes.

The polyhedron made of a combination of polygons having predeterminedshapes may be, e.g., a hexahedron made of a combination of sixtriangular polygons as illustrated in FIG. 11(A), or an octahedron madeof a combination of eight triangular polygons as illustrated in FIG.11(B). The shape of the figure 7 is not limited to particular oneinsofar as the figure shape is a polyhedron made of a combination ofpolygons having predetermined shapes. However, the figure shape ispreferably a hexahedron or an octahedron from the viewpoint of reducingthe computation load and improving the stereoscopic effect inappearance.

(5-2) Shading Process of Figure

In the 3D stereoscopic image, the figure 7 is displayed darker as thefigure is observed on the side closer to the user in a stereoscopicview, and is displayed lighter as the figure is observed on the sidefarther away from the user. A process of changing a shade of the figure7 in such a manner is referred to as a “shading process” hereinafter.

FIG. 12 is a conceptual view of a stereoscopic observation image(hereinafter referred to simply as a “stereoscopic image”) of the figure7 that has been subjected to the shading process. Along a directiondenoted by an arrow in FIG. 12, the figure 7 observed on the side closerto the user is displayed darker, and the figure 7 observed on the sidefarther away from the user is displayed lighter. By executing theshading process of the figure 7 in such a manner, individualstereoscopic items in the 3D stereoscopic image can be displayed with adepth feeling, and the stereoscopic effect in their appearances can beimproved.

A processing method executed in the shading process will be describedwith reference to FIG. 13. A left-eye image and a right-eye image aresimultaneously displayed on the display 43. In a stereoscopic view, theleft-eye image and the right-eye image of a figure 70, which is observedat the position of a screen of the display 43, are displayed in asuperimposed state (see FIG. 13(B)).

When the left-eye image and the right-eye image are displayed on thedisplay 43 such that the left-eye image is positioned on the right sideof the right-eye image (see FIG. 13(A)), the figure is observed on theside closer to the user than the position of the screen of the display43 in a stereoscopic view. In FIG. 13(A), a stereoscopic image of thefigure observed in a state popping out forward of the screen position isdenoted by symbol 71, and the left-eye image and the right-eye image ofthe figure 71, which are displayed on the display 43, are denoted by asymbol 71L and a symbol 71R, respectively. On the other hand, when theleft-eye image and the right-eye image are displayed on the display 43such that the left-eye image is positioned on the left side of theright-eye image (see FIG. 13(C)), the figure is observed on the sidefarther away from the user than the position of the screen of thedisplay 43 in a stereoscopic view. In FIG. 13(C), a stereoscopic imageof the figure observed in a state popping out rearward of the screenposition is denoted by symbol 72, and the left-eye image and theright-eye image of the figure 71, which are displayed on the display 43,are denoted by a symbol 72L and a symbol 72R, respectively.

In the shading process, the left-eye image 71L and the right-eye image71R of the figure 71, which is observed on the side closer to the user,is displayed darker, and the left-eye image 72L and the right-eye image72R of the figure 72, which is observed on the side farther away fromthe user, is displayed lighter.

(5-3) Coordinate Axis

In the 3D stereoscopic image, the coordinate axis is displayed thickerin its portion that is observed on the side closer to the user in astereoscopic view, and is displayed thinner in its portion that isobserved on the side farther away from the user. FIG. 14 is a conceptualview of a stereoscopic image of the coordinate axis displayed in agradually changing thickness. By changing the thickness of thecoordinate axis in such a way, individual stereoscopic items in the 3Dstereoscopic image can be displayed with a depth feeling, and thestereoscopic effect in their appearances can be improved.

Moreover, as illustrated in FIG. 14, the depth feeling on thestereoscopic image can be further increased by displaying a scaleinterval set on the coordinate axis to be wider in a portion that isobserved on the side closer to the user in a stereoscopic view, and tobe narrower in a portion that is observed on the side farther away fromthe user. A similar effect can also be obtained by displaying the name(SS-Lin in FIG. 14) of the coordinate axis and characters denoting scalenumerals (200, 400, 600, 800 and 1000 in FIG. 14) to be larger on theside closer to the user and to be smaller on the side farther away fromthe user. It is to be noted that a process of changing the thickness ofthe coordinate axis, the scale interval, and the character size can beperformed by employing the above-described shading process.

The coordinate axis may be a biexponential axis (see NPL 1) having sucha characteristic that a linear axis (axis representing linearity) and alogarithmic axis are combined with each other. In the case of thebiexponential axis, for data that a measurement value of the parameterselected to be set on the coordinate axis is smaller than apredetermined value, the position of the figure 7 corresponding to themicroparticle is computed by employing a function that includes a linearfunction as a main function element. Further, for data that themeasurement data is larger than the predetermined value, the position ofthe figure 7 is computed by employing a function that includes alogarithmic function as a main function element. For more simplicity,the biexponential axis may include a logarithmic axis assigned to aregion of larger than a predetermined value, and a linear axis assignedto a region of smaller than the predetermined value. By setting thebiexponential axis as the coordinate axis of the three-dimensionaldistribution map, it is possible not only to display a wider dynamicrange by utilizing a characteristic of the logarithmic axis, but also tosimultaneously display a negative number by utilizing a characteristicof the linear axis. Additionally, at least one of the coordinate axes ofthe three-dimensional distribution map may be the biexponential axis.

(5-4) Moving Image

As described above, the three-dimensional distribution map displayed onthe display unit 142 (e.g., the display 43) may be optionally rotated,enlarged, or reduced in accordance with the user's input signal from theinput unit 141 (e.g., the mouse 41 or the keyboard 42). When the 3Dstereoscopic image is rotated, the coordinate axes are preferablydisplayed, as illustrated in FIG. 3, in alignment with respective sidesof a solid shape (cubic in FIG. 3) that constitutes the coordinate space6. Since the solid shape of the coordinate space 6 is more specificallydisplayed by setting the coordinate axes in such a manner, the user canmore easily recognize change in orientation of the three-dimensionaldistribution map when the 3D stereoscopic image is rotated.

The 3D stereoscopic image displayed on the display 43 may be optionallyrotated in accordance with an input from the user, or may be constantlyslowly rotated in a specific direction or an unspecific direction. Bydisplaying the 3D stereoscopic image as a moving image constantlyrotated, the stereoscopic effect in appearance can be increased incomparison with the case displaying a still image.

Moreover, the 3D stereoscopic image displayed on the display 43 can beautomatically turned in accordance with a user's input signal to anorientation, which provides a stereoscopic observation image as viewedfrom the direction of the coordinate axis selected by the user, at anytiming during rotation in accordance with user's manipulation or duringautomatic rotation. FIG. 15 illustrates a stereoscopic observation imageof the three-dimensional distribution map when viewed in a direction ofeach coordinate axis. FIG. 15(A) illustrates an observation image whenviewed in the direction of the Z-axis, FIG. 15(B) illustrates anobservation image when viewed in the direction of the X-axis, and FIG.15(C) illustrates an observation image when viewed in the direction ofthe Y-axis. Switching of a viewing point from the direction of onecoordinate axis to the direction of another coordinate axis may beperformed, for example, such that the viewing point of the image isturned to the direction of the Z-axis upon input of a Z-key from thekeyboard 42 and is turned to the direction of the X-axis from thedirection of the Z-axis upon input of an X-key. Alternatively, theswitching of the viewing point from the direction of one coordinate axisto the direction of another coordinate axis may be performed, forexample, by clicking an icon displayed on the display 43 with the mouse41. By thus enabling the 3D stereoscopic image to be observed while theviewing point is switched from the direction of one coordinate axis tothe direction of another coordinate axis with a simple input operation,the user can more easily understand the characteristic distribution ofmicroparticles in the three-dimensional distribution map.

Furthermore, when the 3D stereoscopic image is displayed on the display43 in a constantly rotated state, the 3D stereoscopic image ispreferably rotated such that an up-and-down direction of thethree-dimensional distribution map is fixedly held. In other words, the3D stereoscopic image is preferably rotated in a state where any oneselected from among an XY-plane, a YZ-plane and a ZX-plane of thethree-dimensional distribution map is always oriented downwards of thedistribution map. More specifically, for example, when the 3Dstereoscopic image illustrated in FIG. 15(A) is constantly rotated, theimage is rotated such that the ZX-plane is always positioned at thebottom of the three-dimensional distribution map. On that occasion, theimage may be rotated while a rotation axis of the three-dimensionaldistribution map is inclined or an inclination angle thereof is changed.By applying a certain restriction to the rotating direction of the 3Dstereoscopic image in such a manner, the user can more easily perceivethe direction of the user's viewing point for the three-dimensionaldistribution map, and can be avoided from failing to recognize theorientation of the three-dimensional distribution map.

The 3D stereoscopic image displayed on the display 43 may be displayedas a moving image in which a figure corresponding to a microparticleswings. In that case, a figure observed on the side closer to the userin a stereoscopic view is displayed to swing over a stroke larger thanthat for the figure 7 observed on the side farther away from to theuser. FIG. 16 is a conceptual view of a stereoscopic image of a figurethat is given with a swinging motion. Figures 71 and 72 are displayedsuch that each figure swings in a right-and-left direction as indicatedby an arrow, and that a swing width in the right-and-left direction isset to be larger for the figure 71 observed on the side closer to theuser and to be smaller for the figure 72 observed on the side fartheraway from the user. By displaying the figure 7 observed on the sidecloser to the user to swing to a larger extent than the figure observedon the side farther away from the user as described above, individualstereoscopic items in the 3D stereoscopic image can be displayed with adepth feeling, and the stereoscopic effect in their appearances can beimproved.

Moreover, when the 3D stereoscopic image is displayed as a moving image,the figure corresponding to the microparticle may be blinked. In thatcase, the stereoscopic effect in appearance of the 3D stereoscopic imagecan be further improved by blinking the figure 7 observed on the sidecloser to the user in a stereoscopic view at a higher frequency than thefigure observed on the side farther away from the user.

In addition, when the measurement data 32 includes measurement values atplural time points, respective 3D stereoscopic images of thethree-dimensional distribution map at the plural time points can bedisplayed as a series of moving images. As a result, for example, in theabove-described case of measuring association or dissociation of amolecular complex on the cell surface, change of the association, etc.of the molecular complex on the cell surface over time can be confirmedwith the series of moving images.

As described above, the 3D data analysis apparatus according to thepresent technique is designed with contrivances to improve thestereoscopic effect in appearance of the displayed 3D stereoscopicimage. Accordingly, even with the three-dimensional distribution mapconsisted of only points (figures corresponding to microparticles) andlines (coordinate axes), the user can analyze the measurement data whilevisually confirming the stereoscopic image with good visibility, and caneasily and intuitively specify microparticles to be analyzed and a smallmass of the microparticle on the distribution map.

6. 3D Data Analysis Program

A 3D data analysis program according to the present technique causes acomputer to execute a step of computing positions and shapes in acoordinate space in which three independent variables selected frommeasurement data of the microparticles are set on coordinate axes, andcreating a 3D stereoscopic image that represents a characteristicdistribution of the microparticles, a step of displaying the 3Dstereoscopic image, and a step of, for each of plural regions of thecoordinate space, which are partitioned by a plane set by a user in the3D stereoscopic image, computing variable values and/or a distributionfrequency in the relevant region.

The following description is made on the basis of the foregoingembodiment by referring to FIGS. 1 and 2 again. The 3D data analysisprogram is stored and held in the hard disk 30 (see symbol 31 in FIG.1). The 3D data analysis program is read into the memory 20 undercontrol of the CPU 10 and the operating system (OS) 33. The 3D dataanalysis program then executes a process of creating the 3D stereoscopicimage of the three-dimensional distribution map in the data processingunit 120 and a process of displaying the 3D stereoscopic image on thedisplay unit 142.

The 3D data analysis program can be recorded on a recording medium thatis readable by a computer. The recording medium is not limitedparticular one on condition that the recording medium is readable by acomputer. For example, a disk-like recording medium, e.g., a flexibledisk or a CD-ROM, is used as the recording medium. As another example, atape-type recording medium, e.g., a magnetic tape, may also be used.

In one example embodiment, a data analysis apparatus comprises: acontrol unit configured to provide data representative of a threedimensional image, the three dimensional image including at least athree dimensional coordinate space which includes at least one planethat divides the three dimensional coordinate space into at least tworegions; a display unit configured to produce the three dimensionalimage based on the data representative of the three dimensional image;and an input unit configured to provide data representative of at leastone of a movement and a position of the at least one plane. In anexample embodiment, first figures representing first data points aredisplayed in at least a first region and second figures representingsecond data points are displayed in at least a second region. In anexample embodiment, the first figures are displayed as different shapesthan the second figures. In an example embodiment, the first figures aredisplayed as hexahedrons and the second figures are displayed asoctahedrons. In an example embodiment, the first figures are displayedin different colors than the second figures. In an example embodiment,the first figures and the second figures are displayed in differentcolors based on a distribution frequency. In an example embodiment, atleast one of the first figures and the second figures are displayed asblinking. In an example embodiment, at least one of variable values anda distribution frequency are calculated for at least one of the firstfigures and the second figures in at least one region. In an exampleembodiment, the three dimensional coordinate space defines adistribution map for data analysis. In an example embodiment, the planeis moveable based on a user manipulation of the input unit to control anindicator figure that is located at a specific point of the threedimensional coordinate space. In an example embodiment, the input unitincludes at least one of a mouse, a keyboard, a touchscreen, a trackpad, a track ball, a touch panel, a joystick, a stylus, a microphone, aspeech recognition unit, and a handheld controller. In an exampleembodiment, the at least one plane is semitransparent. In an exampleembodiment, the at least one plane is set perpendicular to a coordinateaxis. In an example embodiment, the three dimensional coordinate spaceincludes at least two planes that divide the three dimensionalcoordinate space into at least four regions. In an example embodiment,the three dimensional coordinate space includes at least three planesthat divide the three dimensional coordinate space into at least eightregions. In an example embodiment, each of the at least three planes ismoveable based on a user manipulation of the input unit. In an exampleembodiment, an indicator figure for moving each of the at least threeplanes is positioned at an intersection of the at least three planes,and the indicator figure is moveable based on a user manipulation of theinput unit. In an example embodiment, the display unit produces at leasttwo different viewpoints of the three dimensional coordinate space thatare simultaneously displayed. In an example embodiment, the threedimensional image is moveable based on a user manipulation of the inputunit to produce a different viewpoint of the three dimensionalcoordinate space. In an example embodiment, the three dimensional imageis moveable by rotating, enlarging, or reducing the three dimensionalimage. In an example embodiment, the three dimensional image isconstantly moving in at least one of a specific direction and anunspecific direction. In an example embodiment, the at least one planeis selectively displayed based on a user manipulation of the input unit.In an example embodiment, the at least one plane is set oblique to atleast one coordinate axis. In an example embodiment, the data analysisapparatus is a microparticle data analysis apparatus. In an exampleembodiment, the microparticle data analysis apparatus displaysmicroparticle measurement data measured by a flow cytometer. In anexample embodiment, the three dimensional image is a stereoscopic threedimensional image.

In another example embodiment, a data analysis server comprises: a datastorage unit configured to store measurement data; and a data processingunit configured to create data representative of a three dimensionalimage based on the measurement data, the three dimensional imageincluding at least a three dimensional coordinate space which includesat least one plane that divides the three dimensional coordinate spaceinto at least two regions, wherein the at least one plane is moveablebased on data representative of at least one of a movement and aposition of the at least one plane received from an input device. In anexample embodiment, first figures representing first data points aredisplayed in at least a first region and second figures representingsecond data points are displayed in at least a second region. In anexample embodiment, the first figures are displayed as different shapesthan the second figures. In an example embodiment, the first figures aredisplayed as hexahedrons and the second figures are displayed asoctahedrons. In an example embodiment, the first figures are displayedin different colors than the second figures. In an example embodiment,the first figures and the second figures are displayed in differentcolors based on a distribution frequency. In an example embodiment, atleast one of the first figures and the second figures are displayed asblinking. In an example embodiment, at least one of variable values anda distribution frequency are calculated for at least one of the firstfigures and the second figures in at least one region. In an exampleembodiment, the three dimensional coordinate space defines adistribution map for data analysis. In an example embodiment, the planeis moveable based on a user manipulation of an input unit to control anindicator figure that is located at a specific point of the threedimensional coordinate space. In an example embodiment, an input unitincludes at least one of a mouse, a keyboard, a touchscreen, a trackpad, a track ball, a touch panel, a joystick, a stylus, a microphone, aspeech recognition unit, and a handheld controller. In an exampleembodiment, the at least one plane is semitransparent. In an exampleembodiment, the at least one plane is set perpendicular to a coordinateaxis. In an example embodiment, the three dimensional coordinate spaceincludes at least two planes that divide the three dimensionalcoordinate space into at least four regions. In an example embodiment,the three dimensional coordinate space includes at least three planesthat divide the three dimensional coordinate space into at least eightregions. In an example embodiment, each of the at least three planes ismoveable based on a user manipulation of an input unit. In an exampleembodiment, an indicator figure for moving each of the at least threeplanes is positioned at an intersection of the at least three planes,and the indicator figure is moveable based on a user manipulation of aninput unit. In an example embodiment, at least two different viewpointsof the three dimensional coordinate space are simultaneously displayed.In an example embodiment, the three dimensional image is moveable basedon a user manipulation of an input unit to produce a different viewpointof the three dimensional coordinate space. In an example embodiment, thethree dimensional image is moveable by rotating, enlarging, or reducingthe three dimensional image. In an example embodiment, the threedimensional image is constantly moving in at least one of a specificdirection and an unspecific direction. In an example embodiment, the atleast one plane is selectively displayed based on a user manipulation ofan input unit. In an example embodiment, the at least one plane is setoblique to at least one coordinate axis. In an example embodiment, themeasurement data is microparticle measurement data. In an exampleembodiment, the microparticle measurement data is measured by a flowcytometer. In an example embodiment, the three dimensional image is astereoscopic three dimensional image.

In another example embodiment, a data analysis system comprises: ameasurement apparatus; and a data analysis apparatus including: acontrol unit configured to provide data representative of a threedimensional image, the three dimensional image including at least athree dimensional coordinate space which includes at least one planethat divides the three dimensional coordinate space into at least tworegions; a display unit configured to produce the three dimensionalimage based on the data representative of the three dimensional image;and an input unit configured to provide data representative of at leastone of a movement and a position of the at least one plane. In anexample embodiment, first figures representing first data points aredisplayed in at least a first region and second figures representingsecond data points are displayed in at least a second region. In anexample embodiment, the first figures are displayed as different shapesthan the second figures. In an example embodiment, the first figures aredisplayed as hexahedrons and the second figures are displayed asoctahedrons. In an example embodiment, the first figures are displayedin different colors than the second figures. In an example embodiment,the first figures and the second figures are displayed in differentcolors based on a distribution frequency. In an example embodiment, atleast one of the first figures and the second figures are displayed asblinking. In an example embodiment, at least one of variable values anda distribution frequency are calculated for at least one of the firstfigures and the second figures in at least one region. In an exampleembodiment, the three dimensional coordinate space defines adistribution map for data analysis. In an example embodiment, the planeis moveable based on a user manipulation of the input unit to control anindicator figure that is located at a specific point of the threedimensional coordinate space. In an example embodiment, the input unitincludes at least one of a mouse, a keyboard, a touchscreen, a trackpad, a track ball, a touch panel, a joystick, a stylus, a microphone, aspeech recognition unit, and a handheld controller. In an exampleembodiment, the at least one plane is semitransparent. In an exampleembodiment, the at least one plane is set perpendicular to a coordinateaxis. In an example embodiment, the three dimensional coordinate spaceincludes at least two planes that divide the three dimensionalcoordinate space into at least four regions. In an example embodiment,the three dimensional coordinate space includes at least three planesthat divide the three dimensional coordinate space into at least eightregions. In an example embodiment, each of the at least three planes ismoveable based on a user manipulation of the input unit. In an exampleembodiment, an indicator figure for moving each of the at least threeplanes is positioned at an intersection of the at least three planes,and the indicator figure is moveable based on a user manipulation of theinput unit. In an example embodiment, the display unit produces at leasttwo different viewpoints of the three dimensional coordinate space thatare simultaneously displayed. In an example embodiment, the threedimensional image is moveable based on a user manipulation of the inputunit to produce a different viewpoint of the three dimensionalcoordinate space. In an example embodiment, the three dimensional imageis moveable by rotating, enlarging, or reducing the three dimensionalimage. In an example embodiment, the three dimensional image isconstantly moving in at least one of a specific direction and anunspecific direction. In an example embodiment, the at least one planeis selectively displayed based on a user manipulation of the input unit.In an example embodiment, the at least one plane is set oblique to atleast one coordinate axis. In an example embodiment, the measurementapparatus is a microparticle measurement apparatus. In an exampleembodiment, the microparticle measurement apparatus is a flow cytometer.In an example embodiment, the three dimensional image is a stereoscopicthree dimensional image.

In another example embodiment, a computer readable medium storesinstructions which, when executed, cause a data analysis apparatus to:provide data representative of a three dimensional image, the threedimensional image including at least a three dimensional coordinatespace which includes at least one plane that divides the threedimensional coordinate space into at least two regions; and receive aninput providing data representative of at least one of a movement and aposition of the at least one plane. In an example embodiment, firstfigures representing first data points are displayed in at least a firstregion and second figures representing second data points are displayedin at least a second region. In an example embodiment, the first figuresare displayed as different shapes than the second figures. In an exampleembodiment, the first figures are displayed as hexahedrons and thesecond figures are displayed as octahedrons. In an example embodiment,the first figures are displayed in different colors than the secondfigures. In an example embodiment, the first figures and the secondfigures are displayed in different colors based on a distributionfrequency. In an example embodiment, at least one of the first figuresand the second figures are displayed as blinking. In an exampleembodiment, at least one of variable values and a distribution frequencyare calculated for at least one of the first figures and the secondfigures in at least one region. In an example embodiment, the threedimensional coordinate space defines a distribution map for dataanalysis. In an example embodiment, the plane is moveable based on auser manipulation of an input unit to control an indicator figure thatis located at a specific point of the three dimensional coordinatespace. In an example embodiment, an input unit includes at least one ofa mouse, a keyboard, a touchscreen, a track pad, a track ball, a touchpanel, a joystick, a stylus, a microphone, a speech recognition unit,and a handheld controller. In an example embodiment, the at least oneplane is semitransparent. In an example embodiment, the at least oneplane is set perpendicular to a coordinate axis. In an exampleembodiment, the three dimensional coordinate space includes at least twoplanes that divide the three dimensional coordinate space into at leastfour regions. In an example embodiment, the three dimensional coordinatespace includes at least three planes that divide the three dimensionalcoordinate space into at least eight regions. In an example embodiment,each of the at least three planes is moveable based on a usermanipulation of an input unit. In an example embodiment, an indicatorfigure for moving each of the at least three planes is positioned at anintersection of the at least three planes, and the indicator figure ismoveable based on a user manipulation of an input unit. In an exampleembodiment, at least two different viewpoints of the three dimensionalcoordinate space are simultaneously displayed. In an example embodiment,the three dimensional image is moveable based on a user manipulation ofan input unit to produce a different viewpoint of the three dimensionalcoordinate space. In an example embodiment, the three dimensional imageis moveable by rotating, enlarging, or reducing the three dimensionalimage. In an example embodiment, the three dimensional image isconstantly moving in at least one of a specific direction and anunspecific direction. In an example embodiment, the at least one planeis selectively displayed based on a user manipulation of an input unit.In an example embodiment, the at least one plane is set oblique to atleast one coordinate axis. In an example embodiment, the data analysisapparatus is a microparticle data analysis apparatus. In an exampleembodiment, the microparticle data analysis apparatus displaysmicroparticle measurement data measured by a flow cytometer. In anexample embodiment, the three dimensional image is a stereoscopic threedimensional image.

In another example embodiment, a 3D data analysis apparatus comprises: adata storage unit for storing measurement data of microparticles; aninput unit for selecting three independent variables from themeasurement data; a data processing unit for computing positions andfigures in a coordinate space in which the three independent variablesare set on coordinate axes, and creating a 3D stereoscopic image thatrepresents a characteristic distribution of the microparticles; and adisplay unit for displaying the 3D stereoscopic image, wherein a planefor partitioning the coordinate space into plural regions is set in aposition changeable manner and is displayed in the 3D stereoscopic imagein accordance with an input signal from the input unit. In an exampleembodiment, the data processing unit computes variable values and/or adistribution frequency in the region, and the display unit displaysinformation regarding the variable values and/or the distributionfrequency. In an example embodiment, the plane is displayedsemitransparent in the 3D stereoscopic image such that the figurepositioned on a deeper side than the plane can be observed when theimage is observed in a stereoscopic view. In an example embodiment,regarding the 3D stereoscopic image, the plane is displayed in the 3Dstereoscopic image only when a signal is input from the input unit, orwhether the plane is to be displayed or not in the 3D stereoscopic imageis selectable in accordance with an input signal from the input unit. Inan example embodiment, the 3D stereoscopic image is rotated on thedisplay unit in accordance with an input signal from the input unit suchthat the image can be observed in a stereoscopic view from a directionof the optionally selected coordinate axis. In an example embodiment,the plane is a plane perpendicular to the coordinate axis, and aposition of the plane is changed when an indicator figure, which isarranged at an intersection of the plane and the coordinate axis, ismoved in accordance with an input signal from the input unit. In anexample embodiment, the plane comprises three planes perpendicularrespectively to the coordinate axes, and positions of the three planesare changed together when an indicator figure, which is arranged at anintersection of the three planes, is moved in accordance with an inputsignal from the input unit.

In another example embodiment, a microparticle analysis systemcomprises: a 3D data analysis apparatus including a data storage unitfor storing measurement data of microparticles, an input unit forselecting three independent variables from the measurement data, a dataprocessing unit for computing positions and figures in a coordinatespace in which the three independent variables are set on coordinateaxes, and creating a 3D stereoscopic image that represents acharacteristic distribution of the microparticles, and a display unitfor displaying the 3D stereoscopic image, wherein a plane forpartitioning the coordinate space into plural regions is set in aposition changeable manner and is displayed in the 3D stereoscopic imagein accordance with an input signal from the input unit, and amicroparticle measurement apparatus disposed in association with the 3Ddata analysis apparatus.

In another example embodiment, a 3D data analysis method comprises: aprocedure of selecting three independent variables from measurement dataof microparticles; a procedure of computing positions and shapes in acoordinate space in which the three independent variables are set oncoordinate axes, and creating a 3D stereoscopic image that represents acharacteristic distribution of the microparticles; a procedure ofdisplaying the 3D stereoscopic image; and a procedure of setting, in the3D stereoscopic image, a plane for partitioning the coordinate spaceinto plural regions.

In another example embodiment, a 3D data analysis program causes acomputer to execute: a step of computing positions and shapes in acoordinate space in which three independent variables selected frommeasurement data of microparticles are set on coordinate axes, andcreating a 3D stereoscopic image that represents a characteristicdistribution of the microparticles; a step of displaying the 3Dstereoscopic image; and a step of, for each of plural regions of thecoordinate space, which are partitioned by a plane set by a user on the3D stereoscopic image, computing variable values and/or a distributionfrequency in the relevant region.

With the 3D data analysis apparatus according to the present technique,even for a sample which is difficult to analyze by using the knownapparatus using the histogram or the cytogram, accurate analysis resultscan be obtained by setting regions for a data analysis while looking at,in a stereoscopic view, a three-dimensional distribution map in whichthree optionally selected parameters are set on coordinate axes.Therefore, in cooperation with a flow cytometer, for example, the 3Ddata analysis apparatus according to the present technique can be usedto easily and high-accurately analyze characteristics of cells andmicroorganisms in the fields of medical cares, public hygiene, anddevelopment of new medicines.

1: 3D data analysis apparatus, 10: central processing unit, 110: controlunit, 120: data processing unit, 130: data storage unit, 141: inputunit, 142: display unit, 150: input/output interface, 2: flow cytometer,20: memory, 210: control unit, 220: flow system, 230: detection system,231: optical detection unit, 232: electrical detection unit, 240:fractionation unit, 250: input/output interface, 3: microparticleanalysis system, 30: hard disk, 31: 3D data analysis program, 32:measurement data, 33: operating system, 4: communication cable, 41:mouse, 42: keyboard, 43: display, 44: printer, 5: three-dimensionaldistribution map, 51, 52, 53: guide planes, 511, 521, 531, 541:indicator figures, 6: coordinate space, 61, 62, 63, 64, 65, 66, 67, 68:regions, 7: figure, 8: shutter spectacles.

It should be understood by those skilled in the art that variousmodifications, combinations, sub-combinations and alterations may occurdepending on design requirements and other factors insofar as they arewithin the scope of the appended claims or the equivalents thereof.

The application is claimed as follows:
 1. A data analysis apparatus toanalyze microparticle data measured from a flow cytometer comprising: aprocessor configured to produce a three dimensional image based on datarepresentative of the three dimensional image, and the three dimensionalimage represents a characteristic distribution of microparticles in acoordinate space which includes a first coordinate axis, a secondcoordinate axis, a third coordinate axis, and at least two planes thatdivide the three dimensional coordinate space into at least fourregions, wherein a first plane intersects the first coordinate axis andpartitions the three dimensional coordinate space into a first side anda second side by extending across the three dimensional coordinatespace, and a second plane intersects the second coordinate axis andpartitions the three dimensional coordinate space into a third side anda fourth side by extending across the three dimensional coordinatespace, wherein the three dimensional image includes graphicscorresponding to the microparticles in the coordinate space including afirst region with first graphics representing first data points measuredfrom the flow cytometer, a second region with second graphicsrepresenting second data points measured from the flow cytometer, and athird region with third graphics representing third data points measuredfrom the flow cytometer, and wherein the coordinate space defines adistribution map for data analysis, wherein the graphics are displayedin at least one of a different color, size, shape, and mass, and thefirst graphics are displayed differently than the second graphics andthe third graphics, and the second graphics are displayed differentlythan the third graphics, and wherein the distribution map is configuredto analyze the microparticle data.
 2. The data analysis apparatus ofclaim 1, further comprising a display configured to produce the threedimensional image based on the data representative of the threedimensional image.
 3. The data analysis apparatus of claim 1, furthercomprising an input unit configured to provide data representative of atleast one of a movement and a position of at least one plane within thecoordinate space.
 4. The data analysis apparatus of claim 1, wherein afirst distribution frequency is calculated for a first region and asecond distribution frequency is calculated for a second region.
 5. Thedata analysis apparatus of claim 1, wherein at least two regions of thegraphics are displayed in different color and size.
 6. The data analysisapparatus of claim 1, wherein the first graphics, the second graphics,and the third graphics are each positioned within the three dimensionalcoordinate space based on parameter values of the first coordinate axis,the second coordinate axis, and the third coordinate axis.
 7. The dataanalysis apparatus of claim 1, wherein the graphics include firstfigures displayed as different shapes than second figures.
 8. The dataanalysis apparatus of claim 1, wherein the graphics include firstfigures and second figures displayed in different colors based on adistribution frequency.
 9. The data analysis apparatus of claim 1,wherein the graphics include at least one of first figures and secondfigures that are displayed as blinking.
 10. The data analysis apparatusof claim 1, wherein at least one plane in the coordinate space ismoveable to control an indicator figure located at a specific point ofthe coordinate space.
 11. The data analysis apparatus of claim 1,wherein at least one plane in the coordinate space is semitransparent.12. The data analysis apparatus of claim 1, wherein at least one planein the coordinate space is set perpendicular to a coordinate axis. 13.The data analysis apparatus of claim 1, wherein the three dimensionalimage is a stereoscopic three dimensional image.
 14. A data analysisserver to analyze microparticle data measured from a flow cytometercomprising: a memory configured to store measurement data; and aprocessor configured to produce a three dimensional image based on datarepresentative of the three dimensional image, and the three dimensionalimage represents a characteristic distribution of microparticles in acoordinate space which includes a first coordinate axis, a secondcoordinate axis, a third coordinate axis, and at least two planes thatdivide the three dimensional coordinate space into at least fourregions, wherein a first plane intersects the first coordinate axis andpartitions the three dimensional coordinate space into a first side anda second side by extending across the three dimensional coordinatespace, and a second plane intersects the second coordinate axis andpartitions the three dimensional coordinate space into a third side anda fourth side by extending across the three dimensional coordinatespace, wherein the three dimensional image includes graphicscorresponding to the microparticles in the coordinate space including afirst region with first graphics representing first data points measuredfrom the flow cytometer, a second region with second graphicsrepresenting second data points measured from the flow cytometer, and athird region with third graphics representing third data points measuredfrom the flow cytometer, and wherein the coordinate space defines adistribution map for data analysis, wherein the graphics are displayedin at least one of a different color, size, shape, and mass, and thefirst graphics are displayed differently than the second graphics andthe third graphics, and the second graphics are displayed differentlythan the third graphics, and wherein the distribution map is configuredto analyze the microparticle data.
 15. A non-transitory computerreadable medium storing instructions which, when executed, cause a dataanalysis apparatus to analyze microparticle data measured from a flowcytometer to: produce a three dimensional image based on datarepresentative of the three dimensional image, and the three dimensionalimage represents a characteristic distribution of microparticles in acoordinate space which includes a first coordinate axis, a secondcoordinate axis, a third coordinate axis, and at least two planes thatdivide the three dimensional coordinate space into at least fourregions, wherein a first plane intersects the first coordinate axis andpartitions the three dimensional coordinate space into a first side anda second side by extending across the three dimensional coordinatespace, and a second plane intersects the second coordinate axis andpartitions the three dimensional coordinate space into a third side anda fourth side by extending across the three dimensional coordinatespace, wherein the three dimensional image includes graphicscorresponding to the microparticles in the coordinate space including afirst region with first graphics representing first data points measuredfrom the flow cytometer, a second region with second graphicsrepresenting second data points measured from the flow cytometer, and athird region with third graphics representing third data points measuredfrom the flow cytometer, and wherein the coordinate space defines adistribution map for data analysis, wherein the graphics are displayedin at least one of a different color, size, shape, and mass, and thefirst graphics are displayed differently than the second graphics andthe third graphics, and the second graphics are displayed differentlythan the third graphics, and wherein the distribution map is configuredto analyze the microparticle data.